## TFSA-2021-012: `CHECK`-fail in `AddManySparseToTensorsMap`

### CVE Number
CVE-2021-29523

### Impact
An attacker can trigger a denial of service via a `CHECK`-fail in
`tf.raw_ops.AddManySparseToTensorsMap`:

```python
import tensorflow as tf
import numpy as np

sparse_indices = tf.constant(530, shape=[1, 1], dtype=tf.int64)
sparse_values = tf.ones([1], dtype=tf.int64)

shape = tf.Variable(tf.ones([55], dtype=tf.int64))
shape[:8].assign(np.array([855, 901, 429, 892, 892, 852, 93, 96], dtype=np.int64))

tf.raw_ops.AddManySparseToTensorsMap(
    sparse_indices=sparse_indices,
    sparse_values=sparse_values,
    sparse_shape=shape)
```

This is because the
[implementation](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/kernels/sparse_tensors_map_ops.cc#L257)
takes the values specified in `sparse_shape` as dimensions for the output shape:

```cc
    TensorShape tensor_input_shape(input_shape->vec<int64>());
```

The [`TensorShape`
constructor](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188)
uses a `CHECK` operation which triggers when
[`InitDims`](https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296)
returns a non-OK status.

```cc
template <class Shape>
TensorShapeBase<Shape>::TensorShapeBase(gtl::ArraySlice<int64> dim_sizes) {
  set_tag(REP16);
  set_data_type(DT_INVALID);
  TF_CHECK_OK(InitDims(dim_sizes));
}
```

In our scenario, this occurs when adding a dimension from the argument results
in overflow:

```cc
template <class Shape>
Status TensorShapeBase<Shape>::InitDims(gtl::ArraySlice<int64> dim_sizes) {
  ...
  Status status = OkStatus();
  for (int64 s : dim_sizes) {
    status.Update(AddDimWithStatus(internal::SubtleMustCopy(s)));
    if (!status.ok()) {
      return status;
    }
  }
}

template <class Shape>
Status TensorShapeBase<Shape>::AddDimWithStatus(int64 size) {
  ...
  int64 new_num_elements;
  if (kIsPartial && (num_elements() < 0 || size < 0)) {
    new_num_elements = -1;
  } else {
    new_num_elements = MultiplyWithoutOverflow(num_elements(), size);
    if (TF_PREDICT_FALSE(new_num_elements < 0)) {
        return errors::Internal("Encountered overflow when multiplying ",
                                num_elements(), " with ", size,
                                ", result: ", new_num_elements);
      }
  }
  ...
}
```

This is a legacy implementation of the constructor and operations should
use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in
the presence of overflows.

### Patches
We have patched the issue in GitHub commit
[69c68ecbb24dff3fa0e46da0d16c821a2dd22d7c](https://github.com/tensorflow/tensorflow/commit/69c68ecbb24dff3fa0e46da0d16c821a2dd22d7c).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this
commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow
2.1.4, as these are also affected and still in supported range.

### For more information
Please consult [our security
guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for
more information regarding the security model and how to contact us with issues
and questions.

### Attribution
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu
X-Team.
